BACKGROUND: Depressive symptoms display heterogeneous trajectories across adolescence and early adulthood. Identifying risk and protective factors for distinct trajectory groups, and their respective outcomes, may provide insight into the etiological underpinnings of different symptom courses and inform the targets and timing of intervention. METHODS: A school-based sample of 719 adolescents completed four diagnostic evaluations and up to 7 annually mailed questionnaires assessing psychiatric symptoms and psychosocial risk and protective factors. Parental history of psychiatric disorder was assessed. Growth mixture modeling (GMM) was used to identify latent depressive symptom trajectories from mid-adolescence through age 30, as well as their predictors in mid-adolescence and adult outcomes. RESULTS: A three class model consisting of high stable (32%), moderate decreasing (44%), and low decreasing (24%) depressive symptom trajectories emerged as the preferred solution. Demographic, psychosocial, and psychiatric characteristics differentiated the low and high symptom classes, and provided support for interpersonal models of depression chronicity. Members of the moderate and high symptom classes evidenced the worst psychosocial and psychiatric outcomes by age 30, with members of the high symptom class showing the greatest levels of impairment. LIMITATIONS: Cross-sectional measurement and floor effects of several predictor variables may have obscured the relations between those predictors and trajectory class membership. CONCLUSION: These findings suggest that prevention and intervention strategies may specifically target young women and those who experience poor interpersonal functioning in an effort to alter the course of depressive symptoms through early adulthood.
BACKGROUND:Depressive symptoms display heterogeneous trajectories across adolescence and early adulthood. Identifying risk and protective factors for distinct trajectory groups, and their respective outcomes, may provide insight into the etiological underpinnings of different symptom courses and inform the targets and timing of intervention. METHODS: A school-based sample of 719 adolescents completed four diagnostic evaluations and up to 7 annually mailed questionnaires assessing psychiatric symptoms and psychosocial risk and protective factors. Parental history of psychiatric disorder was assessed. Growth mixture modeling (GMM) was used to identify latent depressive symptom trajectories from mid-adolescence through age 30, as well as their predictors in mid-adolescence and adult outcomes. RESULTS: A three class model consisting of high stable (32%), moderate decreasing (44%), and low decreasing (24%) depressive symptom trajectories emerged as the preferred solution. Demographic, psychosocial, and psychiatric characteristics differentiated the low and high symptom classes, and provided support for interpersonal models of depression chronicity. Members of the moderate and high symptom classes evidenced the worst psychosocial and psychiatric outcomes by age 30, with members of the high symptom class showing the greatest levels of impairment. LIMITATIONS: Cross-sectional measurement and floor effects of several predictor variables may have obscured the relations between those predictors and trajectory class membership. CONCLUSION: These findings suggest that prevention and intervention strategies may specifically target young women and those who experience poor interpersonal functioning in an effort to alter the course of depressive symptoms through early adulthood.
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